Perplexity AI on the Writing Efficiency of EFL Students' in Higher Education: Students' Insight
DOI:
https://doi.org/10.29240/ef.v8i1%20May.9982Abstract
Perplexity AI is a powerful machine learning technology that can be utilized to enhance students' writing skills. This study is aimed at investigating the effect of use Perplexed AI in the writing skills process from the perspective of students. This qualitative study employed two primary data collection methods: a modified questionnaire incorporating elements from specific teaching methods or learning approaches and semi-structured interviews. The adapted questionnaire was given to all students in their eighth semester studying English as a Foreign Language (EFL: English as A foreign Language) at a university in North Sumatra Province, and the obtained results include data about how students perceive and navigate the integration of AI in enhancing their writing efficiency within the realm of higher education, as revealed through the perspectives of the students. The results of this research can provide a strong foundation to support the implementation of perplexity artificial intelligence in the context of English language learning at the university level.
Downloads
Downloads
Published
How to Cite
Citation Check
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-NC-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).